Promoting Coordinated Development of Community-Based Information Standards for Modeling in Biology: The COMBINE Initiative

Affiliations

¹ Computing and Mathematical Sciences, California Institute of Technology , Pasadena, CA , USA.
² Auckland Bioengineering Institute, University of Auckland , Auckland , New Zealand.
³ The Donnelly Centre, University of Toronto , Toronto, ON , Canada.
⁴ Computing and Mathematical Sciences, California Institute of Technology , Pasadena, CA , USA ; BioQuant/Centre for Organismal Studies (COS), University of Heidelberg , Heidelberg , Germany.
⁵ Department of Computer Science, University of Oxford , Oxford , UK.
⁶ Computational Biology, Memorial Sloan-Kettering Cancer Center , New York, NY , USA.
⁷ Scientific Databases and Visualization, Heidelberg Institute for Theoretical Studies (HITS) , Heidelberg , Germany.
⁸ Department of Electrical and Computer Engineering, University of Utah , Salt Lake City, UT , USA.
⁹ Faculty of Information Technology, Monash University , Melbourne, VIC , Australia ; Institute of Computer Science, University Halle-Wittenberg , Halle , Germany.
¹⁰ Department of Systems Biology and Bioinformatics, University of Rostock , Rostock , Germany.
¹¹ Babraham Institute , Cambridge , UK ; European Molecular Biology Laboratory-European Bioinformatics Institute , Cambridge , UK.

PMID: 25759811
PMCID: PMC4338824
DOI: 10.3389/fbioe.2015.00019

Review

Promoting Coordinated Development of Community-Based Information Standards for Modeling in Biology: The COMBINE Initiative

Michael Hucka et al. Front Bioeng Biotechnol. 2015.

. 2015 Feb 24:3:19.

doi: 10.3389/fbioe.2015.00019. eCollection 2015.

Authors

Affiliations

¹ Computing and Mathematical Sciences, California Institute of Technology , Pasadena, CA , USA.
² Auckland Bioengineering Institute, University of Auckland , Auckland , New Zealand.
³ The Donnelly Centre, University of Toronto , Toronto, ON , Canada.
⁴ Computing and Mathematical Sciences, California Institute of Technology , Pasadena, CA , USA ; BioQuant/Centre for Organismal Studies (COS), University of Heidelberg , Heidelberg , Germany.
⁵ Department of Computer Science, University of Oxford , Oxford , UK.
⁶ Computational Biology, Memorial Sloan-Kettering Cancer Center , New York, NY , USA.
⁷ Scientific Databases and Visualization, Heidelberg Institute for Theoretical Studies (HITS) , Heidelberg , Germany.
⁸ Department of Electrical and Computer Engineering, University of Utah , Salt Lake City, UT , USA.
⁹ Faculty of Information Technology, Monash University , Melbourne, VIC , Australia ; Institute of Computer Science, University Halle-Wittenberg , Halle , Germany.
¹⁰ Department of Systems Biology and Bioinformatics, University of Rostock , Rostock , Germany.
¹¹ Babraham Institute , Cambridge , UK ; European Molecular Biology Laboratory-European Bioinformatics Institute , Cambridge , UK.

PMID: 25759811
PMCID: PMC4338824
DOI: 10.3389/fbioe.2015.00019

Abstract

The Computational Modeling in Biology Network (COMBINE) is a consortium of groups involved in the development of open community standards and formats used in computational modeling in biology. COMBINE's aim is to act as a coordinator, facilitator, and resource for different standardization efforts whose domains of use cover related areas of the computational biology space. In this perspective article, we summarize COMBINE, its general organization, and the community standards and other efforts involved in it. Our goals are to help guide readers toward standards that may be suitable for their research activities, as well as to direct interested readers to relevant communities where they can best expect to receive assistance in how to develop interoperable computational models.

Keywords: biology; computational modeling; data sharing; file formats; reproducible science; standardization.

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Promoting Coordinated Development of Community-Based Information Standards for Modeling in Biology: The COMBINE Initiative

Affiliations

Promoting Coordinated Development of Community-Based Information Standards for Modeling in Biology: The COMBINE Initiative

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Abstract

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